Epigenetics is not Lamarckian. There are ways in which it mimics, badly, some features of Lamarckian evolution, but it’s its own thing that has unpredicable, non-Lamarckian side-effects. The only way Lamarck’s speculation can be resurrected is through intervention by the kind of genetic engineering that we aren’t sure is possible yet. A genome is the great grandaddy rats’ nest of all rats’ nests, and giving a creature a long-ass neck in a lab is probably more work for less reward than the original 100,000 generations accomplished in making a giraffe that worked.
What Mr. Plasma should do, instead of trying to dig himself out of the classification of internet troll, is come up with experiments that demonstrate his ideas in the lab, on the one hand, or observe the plasma lab of space directly and establish that it exists to the extent that he believes it does. At this point all he’s doing is hoping that people will think “plate tectonics? that turned out okay, maybe this could too.” Frankly, it isn’t interesting.
I try to distinguish Sheldrake’s original ideas from his discussion of philosophy. I find his philosophical perspective to be of incredible significance, and am far less interested in his original theories. But, I also try to go out of my way to not permit myself to formulate certainty on the issue, for the very reason that I understand that my knowledge on this topic remains unorganized and unsupported by an appreciation for the argumentation.
What he says about the mechanistic worldview is, based upon my own observations of people online, spot on. This problem is not only pertinent to astrophysics & cosmology. A review of the work of Gerald Pollack of the University of Washington reveals that it also dominates in biology – and this should be of critical importance to people, for our medical practices are founded on this notion that the body is fundamentally a mechanical device. The very idea that every cell membrane contains miniature ionic pumps and channels is truly a quaint idea, given what we know about gels and polymers today. There are many, many strong arguments which can be put forth against it. The study of water has unfortunately been cast away as serious science, due to the polywater debacle. That perception problem ultimately obscures the fascinating, unconventional science underlying water. Pollacks’ YouTube talks are very thought-provoking.
Electricity is extraordinarily efficient when it comes to the behavior of gels – which the body is. Eyebrows should naturally raise when somebody suggests that it takes a mechanical device to move electricity. That’s not saying much for evolution, for we can make far more efficient systems in the laboratory with polymer phase transitions. There seems to be a willingness to think that we can create things in the laboratory which mother nature is blind to. That’s probably human arrogance talking.
There is a consistent misperception that experimental and observational support for the EU does not exist. Yet, plasma physics is quite an advanced science at this point, plasma scaling is a known phenomenon distinct from the EU, and the EU uses plasma scaling to suggest fundamental physics explanations for enigmas which – despite all of our technology – continue to plague modern astrophysics & cosmology.
There really is an information problem here. I went through this process of learning the EU, and what I found bothered me quite a bit. The process of taking the idea seriously consumed 8 years of my life. And this really raises very serious questions about what we expect a new emergent idea in science to look like. We have a general expectation that we would appreciate the value of an idea if we saw it, but then if you look at the way that people evaluate new ideas in science, what I’ve seen is that they don’t use the proper criteria. People tend to judge new ideas in science based upon their divergence from established theories, and then they apply a non-rational process (known as associative coherence) to reason, for instance, that the scientific community could not have possibly made such a huge error. I’ve studied many hundreds of scientific discourse threads. People tend to get a sense very early on with the EU that to formulate a truly meaningful opinion of this idea, they would have to do an incredible amount of investigation. Our minds exhibit a complex reaction to this realization, which is best described by the work of Nobel laureate Daniel Kahneman. Phil Barden’s book Decoded takes Kahneman’s theory and applies it to marketing. Taken together, these two resources are going to turn out to be incredibly important for the design of scientific discourse systems which keep our conversations rational.
The evidence for the EU is wrapped up in thick jargon …
plasma
critical ionization velocity (CIV)
Marklund convection
the solar corona’s inverse temperature enigma
electric fields
magnetic fields
double layers
HI hydrogen
radio astronomy countour maps
high-velocity clouds
(etc)
So, this raises a very serious question: If people cannot even understand the terms being used to describe the experimental evidence, then what meaning can the evidence have for people?
This is why I advocate for the creation of a knowledge graph as an infrastructure for the evidence & argumentation. Frankly, we have very serious work to be done on the information visualization aspect of scientific discourse. And this is why I’m here: I came here with some appreciation for the design needs for a scientific social network, after already having put 3 years of research into this site. My intent has been from the start to meet web designers.
The problem of scientific discourse today is that there is no path for new ideas which involve questioning our initial hypotheses to emerge today. These ideas are filtered out at the peer review process. They don’t make it into our popular science programs. Science journalists won’t touch them because that risks their scientific contacts. The culture online rejects them because of the current focus upon pseudoscience. The textbooks generally limit their discussions to the conclusions of scientists. The only option at this point is vanity press publication and journals dedicated to such ideas – which, in a general sense, nobody reads.
So, what I am doing is visualizing discourse in ways that have not yet been tried, like this …
And this is not just something that I made up. Concept mapping has been empirically demonstrated to be an effective pedagogical tool, when used properly. This is a very rudimentary prototype, but the more I study this, the more that I see that much of this design can be implemented using scalable vector graphics in HTML5.
If I sent all of that information at you in pure text, you would immediately lose interest. The switch to a graphical format is much easier on the eyes, and sets into motion a completely different, more constructive set of subconscious reactions.
So, what is really important to do here is to not over-focus upon whether or not the EU and other fringe ideas are actually supported by evidence. The first step to making that evaluation is to build systems which permit us to talk about science in ways which support the emergence of the long tail in scientific discourse. Then, once we have a path for emergence in science, we can then focus upon a visualization approach to moderation. We want the best, most scientific arguments to percolate to the top of the visualization. Accordingly, concept mapping and a new system for rating contributions tend to go hand-in-hand. There is no need to censor views in science. We can simply apply scientific standards to mediate which contributions are most visible. But, the key here is to not let ideological preferences interfere with this process at the level of worldviews. When we are clashing worldviews, we are bound to being agnostic on the worldview if our goal is to create a path for innovative ideas in science to emerge.
There is a risk that by taking a very traditionalist approach to scientific discourse, that we will fail to utilize the technologies which are now at our disposal for sifting through information. The genuine opportunities for a scientific social network are actually quite significant at this point for the very reason that everybody is so focused upon simplistic filters in discourse that dichotomize everything as either science or pseudoscience. We have all of these standards for rating ideas in science today – philosophy of science, Mertonian norms (the “scientific attitude”) and critical thinking standards for identifying biases, are the three primary types. The fact that people still consider thumbs up and down on Slashdot to be some sort of innovation is really kind of laughable. That’s 2,000-year-old “technology” at this point. Most know it as mob rules, and it should be clear by now that mobs oftentimes make mistakes. We can do much, much better than thumbs up and down.
This is what’s exciting for me. I don’t code, unfortunately. As a writer I am constantly frustrated by the terribly bad tools coders make for editing and working with ideas, and the terribly bad decisions they make in industry-standard tools like Word. Another example is the fact that Sili-Valley tech elites constantly complain about how antiquated math education is when the infrastructure they built, the infrastructure they congratulate themselves about constantly, doesn’t allow people to do basic things like play with math equations and visualizations. Instead those issues are part of a niche market locked down by patents and very defensive, closed-source companies like Wolfram and Autodesk. If children could send math equations and data and plots to each other via SMS on their phones, if classrooms weren’t chained to what remains the most straightforward pedogogical tool for math, the whiteboard, math education and understanding would advance.
As you say, if this were to change, the web’s ability to make an end-run around institutional stasis would advance more thoroughly into scientific and social-science fields. The text-based diversity of opinion and discourse we’ve developed on the web is still profoundly limited by the inability to properly talk econ and science. It’s too easy for people’s eyes to glaze over when confronted with new ideas (as mine did when looking through your comments above), and too easy to bury discourse under a mountain of reflexive, gestural restatement of what everyone already “knows”.
All that said, the map you posted seems to address only one part of the issue, the debating part. I would hesitate to call it pedagogy. The thing that would make it pedagogy is a map that does a better job of conveying your actual 99th percentile science to 96th percentile minds like mine. That would require the development in the online culture of conventions for how to visualize and explore multidimensional data sets and the mathematical models that might account for them.
I’m going to go hunt for some concept-mapping software so I can fiddle with it.
This is insightful. I have indeed left huge chunks out.
But, let’s review some of the underlying reasons for all of this …
(1) One of the things happening in science education right now is a gradual epistemological transition which the inventor of concept maps, Joseph Novak, prefers to contrast with positivism and constructivism. Positivism, in his view, is the one-way discourse we see with the lecture format. It positions knowledge as purely objective, and the process of learning, in this view, is to get that objective knowledge into the minds of students.
Constructivism is the alternative view that for particularly complex topics with no obvious resolution, we should focus upon the quality of discourse rather than the conclusions of scientists. It positions learning at all stages as heavily dependent upon discourse; it strives to spread assessments out, even within the lectures themselves (like Eric Mazur’s “peer instruction”); and it emphasizes the role of concepts to the process of assimilation. In this view, a distinction is made between assimilation of new information and rote memorization. Concept maps are a necessary and proven tool for updating and modifying concepts in the brain.
(2) Physics education researchers (PER) like Eric Mazur and David Hestenes have observed very serious problems with peoples’ ability to learn basic mechanics physics principles, based upon the force concept inventory (FCI) test. The problem is the “intuitive notions” which students bring to the classes, which keep them from hurting themselves. We all develop intuitive notions in physics as a natural reaction to our observed environments. It turns out that instruction which does not address these intuitions is ineffective for about 90% of the people. What I’ve personally observed is that this is largely what distinguishes people who are able to question scientific theories from those who are not. The ones who cannot question theory failed to assimilate the knowledge into their long-term knowledge structures. Instead, what they did was create separate knowledge structures which lack interconnections with the knowledge structure they use to problem-solve in everyday life. Concept maps are perfect for addressing this problem.
(3) One of my own observations is that people do not understand what a worldview in science is. And this strongly suggests that people do not understand the structure of scientific theory itself. There are properties; concepts which contain them; propositions which relate multiple concepts; models (aka theories) which contain sets of propositions; and at the very top of all of this are worldviews – which is basically anything that is happening within the mind of a thinker.
Now, something very important can be observed online with regards to worldviews and models: People who are trying to talk about models do not like to be in the same room with people who are talking about worldviews, and vice-versa. There is a very important reason for this that doesn’t become apparent until a person studies how innovation is done in the business world: The point of building models is to converge, whereas with worldview clashes, divergence is just as valued. What this suggests is that scientific discourse is not just one process. It’s a system of systems. If our discourse system is to support the repeating innovation cycle of divergence & convergence, we cannot let one of these two processes dominate the other. In other words, they should happen in two separate places.
(4) One of the biggest problems with emergence in scientific discourse is the fact that people trying to make a case against conventional theory are given a blank text box to make their case. This basically favors conventional wisdom & the status quo, as it’s nearly impossible to undermine conventional theory from scratch with only text. It really doesn’t matter what arguments are put forward: Making a strong case requires huge amounts of text, but huge amounts of text will not be read. We have to start viewing text as having an inherent cost associated with it. Think about it this way: Text is like lots of little graphics. The mind has to interpret each of these lines and curves, and not only assemble them into characters, then words, then sentences and paragraphs, but it also has to process the meaning of all of that. When possible, we need to be using graphics to make our case.
And on top of that, there is absolutely no reason that we should be starting from scratch every time. The arguments are all out there on the web, in books, videos and scientific papers (etc). It makes no sense to repeat the same laborious process of fetching them each time. We need to build a knowledge graph, and this knowledge graph should be very carefully designed to support emergence in scientific discourse.
(5) What I would suggest is that the mathematics should be layered on top of this conceptual substructure. That’s because the large majority of people – if not everybody – organize their knowledge on the basis of the concepts, not the mathematics. The concepts are fundamental. And in fact, when paradigm changes do actually occur, they tend to involve changes to the concepts. So, until we build systems which support our own ability thoroughly reflect upon this epistemological structure to science, paradigm changes will remain unsupported by our communication technologies.
This is pretty much why I’m not just agnostic, but fundamentalist about it - I consider the opinions of anyone who isn’t agnostic to be tainted. Of course, I have my own share of cognitive biases and what have you that interfere with acheiving a completely agnostic perspective, but the main thing is to acknowledge the point in the first place, and be open to working towards it. In my book, it’s just another example of the sort of culture that makes the difference between grunting animals and advanced civilisation.
So I tend not to simply reject anything I can’t easily understand; that requires a lot of hubris, if you can do ontology. Particularly given the many examples in the history of science of low-hanging fruit that went unpicked for too long, simply because peoples’ dominant paradigm didn’t easily accomodate it. There is vast opportunity to be had in mass agnosticism; I dearly hope to see an inkling of it one day.
The problem of scientific discourse today is that there is no path for new ideas which involve questioning our initial hypotheses to emerge today. These ideas are filtered out at the peer review process. They don’t make it into our popular science programs. Science journalists won’t touch them because that risks their scientific contacts. The culture online rejects them because of the current focus upon pseudoscience. The textbooks generally limit their discussions to the conclusions of scientists. The only option at this point is vanity press publication and journals dedicated to such ideas – which, in a general sense, nobody reads.
A significantly more effective means of doing science is a magnificent goal, and again, something that would be a lot easier to achieve if it weren’t for everybody’s damn cognitive biases and logical fallacies, particularly the assumption that things aren’t broke so people proposing fixes aren’t worth listening to…
But it seems like an easier sell than a concept you admit pretty much requires this more effective means to sell. So why the huge emphasis on plasma cosmology if there’s this intervening priority of recruiting coders to build a venue to give this idea and others a fighting chance? I’m pretty sure that if you’d poured all that effort into illustrating this fundamental problem and proposing your solution, you’d have achieved more traction by now - there are more coders than cosmologists reading BB. And the lack of an optimised battleground for scientific ideas is unquestionably a bigger problem than mistaken cosmology IMO.
Something I’ve noticed that’s common to many success stories is the flexibility that enabled them - someone starts off trying to achieve X, but hits a few speed bumps that’d stop many in their tracks… but without tunnel vision restricting the outcome, the lessons of failure prompt Y to be conceived as a goal instead. And here, Y could facilitate X.
The thing is this: People are getting way too hung up on formulating a conclusion about ideas which compete with conventional theories. My thesis is that the way in which we talk about science has a dominant influence upon the quality of the discourse. It’s actually obvious, once you think about it – for if we were still using Morse code, the conversations would be even that much worse.
So, my own take is that we should never expect a system which has not been designed to support the emergence and evidential support of new ideas to just nevertheless result in emergence and accurate beliefs. Support for emergence must be designed; then, when it occurs, it must be captured; and once it’s captured, it must be identified and visualized to have priority. Without tools to do this, emergence just becomes buried in the heap. Accuracy in belief requires a collective effort to vet and contribute knowledge in a constructive manner. The threads never make it to this point. They weren’t designed to do this. What we have today is fundamentally designed to support the status quo – whether intentional or not.
What I try to tell people is that if the goal is to create a tool for innovation in science, then the way to do that is to study the ways in which the discourse about against-the-mainstream ideas in science tend to derail. What you will observe is that – even if the competing idea is not correct, which is actually irrelevant – the observed reasons for rejecting the idea will tend to be wrong. That’s because the actual debate amongst theorists is always more complex than the threads you see online. This is particularly easy to demonstrate with the Electric Universe. People are going to be completely taken by surprise by the number of rebuttals which exist, and which are not being pointed to in these threads.
The point here is that people who are focused on the conclusions over the quality of discourse are not trying to design a scientific social network. The site design is what matters. Build the site, and only then should people be formulating conclusions, once we have a system which does not fundamentally favor the status quo.
You might want to take a look at Brian Koberlein’s quasi-recent “analysis” of the Electric Universe, for which I posted some early shots of my own analysis …
A scientific social network meets its acid test on controversy.
Pay close attention to this article & thread. It exemplifies everything that is wrong with scientific discourse today. Once you see the amount of information that is directly pertinent to the conversation that does not get mentioned, you will start to understand the problem.
But, go ahead and digest the thread without all of that first. Give it a pass. You should be able to recognize at least one critical problem w/o any help.
